Loss Gap Parity for Fairness in Heterogeneous Federated Learning

Brahim Erraji, Michaël Perrot, Aurélien Bellet

While clients may join federated learning to improve performance on data they rarely observe locally, they often remain self-interested, expecting the global model to perform well…